Named entity recognition in query

11 years 8 months ago
Named entity recognition in query
This paper addresses the problem of Named Entity Recognition in Query (NERQ), which involves detection of the named entity in a given query and classification of the named entity into predefined classes. NERQ is potentially useful in many applications in web search. The paper proposes taking a probabilistic approach to the task using query log data and Latent Dirichlet Allocation. We consider contexts of a named entity (i.e., the remainders of queries after the named entity is removed) as words of a document, and classes of the named entity as topics. The topic model is constructed by a novel and general learning method referred to as WS-LDA (Weakly Supervised Latent Dirichlet Allocation), which employs weakly supervised learning (rather than unsupervised learning) using partially labeled seed entities. Experimental results show that the proposed method based on WS-LDA can accurately perform NERQ, and outperform the baseline methods. Categories and Subject Descriptors H.3.3 [Informa...
Jiafeng Guo, Gu Xu, Xueqi Cheng, Hang Li
Added 28 May 2010
Updated 28 May 2010
Type Conference
Year 2009
Authors Jiafeng Guo, Gu Xu, Xueqi Cheng, Hang Li
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